SoroushVahidi/scidocs huggingface dataset:
Secure Communication Method Based on Encryption and Steganography
(2017)

Encryption is a traditional method of scrambling data beyond recognition. For years, encryption has been widely used in various areas and domains where secrecy and confidentiality were required. However, there are certain encryption techniques that are not allowed in some countries. In these cases, steganography may come as a solution for hiding data using an apparently inoffensive and innocent carrier. The purpose of steganography is to deliver secret information from a sender to a receiver by scrambling the communication channel not the information itself. This way, it is very unlikely for someone to identify and extract the secret message without knowing exactly how it was embedded into the carrier. Moreover, this task is more difficult since most steganographic methods rely on file or packet header redundancy, lossy multimedia algorithms or insignificant content alteration. All of these are very hard to detect. In this paper, a combination of encryption with image based steganography is presented in order to offer similar robustness as offered by advanced encryption algorithms such as RSA, AES or DES but with lower resource needs. The most original contribution of this paper consists in how a secret message is embedded into a image carrier generating 3 different but very similar images. These images are sent to the destination using different channels and then used to recover the original (secret) message.
Jigsaw: indoor floor plan reconstruction via mobile crowdsensing
(2014)

The lack of floor plans is a critical reason behind the current sporadic availability of indoor localization service. Service providers have to go through effort-intensive and time-consuming business negotiations with building operators, or hire dedicated personnel to gather such data. In this paper, we propose Jigsaw, a floor plan reconstruction system that leverages crowdsensed data from mobile users. It extracts the position, size and orientation information of individual landmark objects from images taken by users. It also obtains the spatial relation between adjacent landmark objects from inertial sensor data, then computes the coordinates and orientations of these objects on an initial floor plan. By combining user mobility traces and locations where images are taken, it produces complete floor plans with hallway connectivity, room sizes and shapes. Our experiments on 3 stories of 2 large shopping malls show that the 90-percentile errors of positions and orientations of landmark objects are about 1~2m and 5~9°, while the hallway connectivity is 100% correct.
Dielectric properties of human normal, malignant and cirrhotic liver tissue: in vivo and ex vivo measurements from 0.5 to 20 GHz using a precision open-ended coaxial probe.
(2007)

Hepatic malignancies have historically been treated with surgical resection. Due to the shortcomings of this technique, there is interest in other, less invasive, treatment modalities, such as microwave hepatic ablation. Crucial to the development of this technique is the accurate knowledge of the dielectric properties of human liver tissue at microwave frequencies. To this end, we characterized the dielectric properties of in vivo and ex vivo normal, malignant and cirrhotic human liver tissues from 0.5 to 20 GHz. Analysis of our data at 915 MHz and 2.45 GHz indicates that the dielectric properties of ex vivo malignant liver tissue are 19 to 30% higher than normal tissue. The differences in the dielectric properties of in vivo malignant and normal liver tissue are not statistically significant (with the exception of effective conductivity at 915 MHz, where malignant tissue properties are 16% higher than normal). Also, the dielectric properties of in vivo normal liver tissue at 915 MHz and 2.45 GHz are 16 to 43% higher than ex vivo. No statistically significant differences were found between the dielectric properties of in vivo and ex vivo malignant tissue (with the exception of effective conductivity at 915 MHz, where malignant tissue properties are 28% higher than normal). We report the one-pole Cole-Cole parameters for ex vivo normal, malignant and cirrhotic liver tissue in this frequency range. We observe that wideband dielectric properties of in vivo liver tissue are different from the wideband dielectric properties of ex vivo liver tissue, and that the in vivo data cannot be represented in terms of a Cole-Cole model. Further work is needed to uncover the mechanisms responsible for the observed wideband trends in the in vivo liver data.
Camera parameters auto-adjusting technique for robust robot vision
(2010)

How to make vision system work robustly under dynamic light conditions is still a challenging research focus in computer/robot vision community. In this paper, a novel camera parameters auto-adjusting technique based on image entropy is proposed. Firstly image entropy is defined and its relationship with camera parameters is verified by experiments. Then how to optimize the camera parameters based on image entropy is proposed to make robot vision adaptive to the different light conditions. The algorithm is tested by using the omnidirectional vision in indoor RoboCup Middle Size League environment and the perspective camera in outdoor ordinary environment, and the results show that the method is effective and color constancy to some extent can be achieved.
Image Processing And Pattern Recognition Fundamentals And Techniques
(2013)

It's coming again, the new collection that this site has. To complete your curiosity, we offer the favorite image processing and pattern recognition fundamentals and techniques book as the choice today. This is a book that will show you even new to old thing. Forget it; it will be right for you. Well, when you are really dying of image processing and pattern recognition fundamentals and techniques, just pick it. You know, this book is always making the fans to be dizzy if not to find.
Rules for an Ontology-based Approach to Adaptation
(2006)

Adaptation addresses the complexity and overload caused by an increasing amount of available resources by the identification and presentation of relevant resources. Drawbacks of existing approaches to this end include the limited degree of customization, difficulties in the acquisition of model information and the lack of control and transparency of the system's adaptive behavior. This paper proposes an approach which addresses these drawbacks to perform meaningful and effective adaptation by the application of semantic Web technologies. This comprises the use of an ontology and adaptation rules for knowledge representation and inference engines for reasoning. The focus of this paper lies in the presentation of adaptation rules
RTL implementation and analysis of fixed priority, round robin, and matrix arbiters for the NoC's routers
(2016)

Networks-on-Chip (NoC) is an emerging on-chip interconnection centric platform that influences modern high speed communication infrastructure to improve the performance of many-core System-on-Chip (SoCs) designs. The core of each NoCs router involves arbiter and multiplier pairs that need to be carefully co-optimized in order to achieve an overall efficient implementation. Low transmission latency design is one of the most important parameters of NoC design. This paper uses parametric Verilog HDL to implement the designs and compares the performance in terms of power, area, and delay of different types of arbiters using for NoCs routers. The RTL implementation is performed using parametric Verilog HDL and analysis in term of power, area and delay is performed using Xilinx ISE 14.7 and Xpower Analyzer (XPA) with Xpower Estimator (XPE). The target device uses for these implementation is Vertex 6.
[Translation and validation for Brazil of the body image scale for adolescents--Offer Self-Image Questionnaire (OSIQ)].
(2011)

OBJECTIVE
To evaluate the semantic and measure equivalence of the body image sub-scale of the Offer Self Image Questionnaire (OSIQ).


METHODS
Participants were 386 teenagers, 10 to 18 years old, both sexes, enrolled in a private school (junior and high school age). Translation, back-translation, technique revision and evaluation were conducted. The Portuguese instrument was evaluated for internal consistency, discriminate and concurrent validity.


RESULTS
Internal consistency showed values from 0.43 to 0.54 and was able to discriminate all groups studied--the whole population, boys and girls, and boys in early adolescence, by nutritional status (p<0.001; p<0.009; p=0.030; p=0.043, respectively). Concurrent analyses showed significant correlation with anthropometric measures only for girls (r=-0.16 and p=0.021; r=-0.19 and p=0.007), early adolescence (r=-0.23 and p=0.008; r=-0.26 and p=0.003) and intermediate adolescence (r=-0.29 and p=0.010) and the retest confirmed reliability by the coefficient of interclass correlation. Although the instrument has proven its ability to discriminate between the groups studied by nutritional state, other results were less satisfactory. More studies are necessary for full transcultural adaptation, including the application of other comparative scales.


CONCLUSION
The body image sub-scale of the OSIQ was translated, but the results are not promising and require more studies.
Inflammatory reaction to hyaluronic acid: A newly described complication in vocal fold augmentation.
(2017)

OBJECTIVES/HYPOTHESIS
To establish the rate of inflammatory reaction to hyaluronic acid (HA) in vocal fold injection augmentation, determine the most common presenting signs and symptoms, and propose an etiology.


STUDY DESIGN
Retrospective chart review.


METHODS
Patients injected with HA over a 5-year period were reviewed to identify those who had a postoperative inflammatory reaction. Medical records were reviewed for patient demographic information, subjective complaints, Voice Handicap Index-10 (VHI-10) scores, medical intervention, and resolution time. Videolaryngostroboscopy examinations were also evaluated.


RESULTS
A total of 186 patients (245 vocal folds) were injected with HA over a 5-year period, with a postoperative inflammatory reaction rate of 3.8%. The most common complaints in these patients were odynophagia, dysphonia, and dyspnea with vocal fold erythema, edema, and loss of pliability on videolaryngostroboscopy. All patients were treated with corticosteroids. Return of vocal fold vibration ranged from 3 weeks to 26 months, with VHI-10 scores normalizing in 50% of patients.


CONCLUSIONS
This reaction may be a form of hypersensitivity related to small amounts of protein linked to HA. Alternatively, extravascular compression from the HA could lead to venous congestion of the vocal fold. The possibility of equipment contamination is also being investigated. Further studies are needed to determine the etiology and best treatment.


LEVEL OF EVIDENCE
4 Laryngoscope, 2016 127:445-449, 2017.
Global effects of smoking, of quitting, and of taxing tobacco.
(2014)

From the Center for Global Health Research, St. Michael’s Hospital and Dalla Lana School of Public Health, University of Toronto, Toronto (P.J.); and the Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, Richard Doll Building, University of Oxford, Oxford, United Kingdom (R.P.). Address reprint requests to Dr. Jha at prabhat.jha@utoronto.ca.
User-centered security: stepping up to the grand challenge
(2005)

User-centered security has been identified as a grand challenge in information security and assurance. It is on the brink of becoming an established subdomain of both security and human/computer interface (HCI) research, and an influence on the product development lifecycle. Both security and HCI rely on the reality of interactions with users to prove the utility and validity of their work. As practitioners and researchers in those areas, we still face major issues when applying even the most foundational tools used in either of these fields across both of them. This essay discusses the systemic roadblocks at the social, technical, and pragmatic levels that user-centered security must overcome to make substantial breakthroughs. Expert evaluation and user testing are producing effective usable security today. Principles such as safe staging, enumerating usability failure risks, integrated security, transparent security and reliance on trustworthy authorities can also form the basis of improved systems
Static and Moving Object Detection Using Flux Tensor with Split Gaussian Models
(2014)

In this paper, we present a moving object detection system named Flux Tensor with Split Gaussian models (FTSG) that exploits the benefits of fusing a motion computation method based on spatio-temporal tensor formulation, a novel foreground and background modeling scheme, and a multi-cue appearance comparison. This hybrid system can handle challenges such as shadows, illumination changes, dynamic background, stopped and removed objects. Extensive testing performed on the CVPR 2014 Change Detection benchmark dataset shows that FTSG outperforms state-of-the-art methods.
A Quick Tour of BabelNet 1.1
(2013)

In this paper we present BabelNet 1.1, a brand-new release of the largest “encyclopedic dictionary”, obtained from the automatic integration of the most popular computational lexicon of English, i.e. WordNet, and the largest multilingual Web encyclopedia, i.e. Wikipedia. BabelNet 1.1 covers 6 languages and comes with a renewed Web interface, graph explorer and programmatic API. BabelNet is available online at http://www.babelnet.org.
Cloud Computing: The impact on digital forensic investigations
(2009)

Cloud Computing (CC) as a concept and business opportunity is likely to see many organisations experiencing the 'credit crunch', embrace the relatively low cost option of CC to ensure continued business viability and sustainability. The pay-as-you-go structure of the CC business model is typically suited to SME's who do not have the resources to completely fulfil their IT requirements. Private end users will also look to utilise the colossal pool of resources that CC offers in an attempt to provide mobile freedom of information. However, as with many opportunities that offer legitimate users enormous benefits, unscrupulous and criminal users will also look to use CC to exploit the loopholes that may exist within this new concept, design and business model. This paper will outline the tasks that the authors undertook for the CLOIDIFIN project and highlight where the Impact of CC will diversely effect digital forensic investigations.
An Improvement to Feature Selection of Random Forests on Spark
(2014)

The Random Forests algorithm belongs to the class of ensemble learning methods, which are common used in classification problem. In this paper, we studied the problem of adopting the Random Forests algorithm to learn raw data from real usage scenario. An improvement, which is stable, strict, high efficient, data-driven, problem independent and has no impact on algorithm performance, is proposed to investigate 2 actual issues of feature selection of the Random Forests algorithm. The first one is to eliminate noisy features, which are irrelevant to the classification. And the second one is to eliminate redundant features, which are highly relevant with other features, but useless. We implemented our improvement approach on Spark. Experiments are performed to evaluate our improvement and the results show that our approach has an ideal performance.
Yield Trends Are Insufficient to Double Global Crop Production by 2050
(2013)

Several studies have shown that global crop production needs to double by 2050 to meet the projected demands from rising population, diet shifts, and increasing biofuels consumption. Boosting crop yields to meet these rising demands, rather than clearing more land for agriculture has been highlighted as a preferred solution to meet this goal. However, we first need to understand how crop yields are changing globally, and whether we are on track to double production by 2050. Using ∼2.5 million agricultural statistics, collected for ∼13,500 political units across the world, we track four key global crops-maize, rice, wheat, and soybean-that currently produce nearly two-thirds of global agricultural calories. We find that yields in these top four crops are increasing at 1.6%, 1.0%, 0.9%, and 1.3% per year, non-compounding rates, respectively, which is less than the 2.4% per year rate required to double global production by 2050. At these rates global production in these crops would increase by ∼67%, ∼42%, ∼38%, and ∼55%, respectively, which is far below what is needed to meet projected demands in 2050. We present detailed maps to identify where rates must be increased to boost crop production and meet rising demands.
Characterizing affective instability in borderline personality disorder.
(2002)

OBJECTIVE
This study sought to understand affective instability among patients with borderline personality disorder by examining the degree of instability in six affective domains. The authors also examined the subjective intensity with which moods are experienced and the association between instability and intensity of affect.


METHOD
In a group of 152 patients with personality disorders, subjective affective intensity and six dimensions of affective instability were measured. The mean scores for lability and intensity for each affective domain for patients with borderline personality disorder were compared with those of patients with other personality disorders through analyses that controlled for other axis I affective disorders, age, and sex.


RESULTS
Greater lability in terms of anger and anxiety and oscillation between depression and anxiety, but not in terms of oscillation between depression and elation, was associated with borderline personality disorder. Contrary to expectation, the experience of an increase in subjective affective intensity was not more prominent in patients with borderline personality disorder than in those with other personality disorders.


CONCLUSIONS
By applying a finer-grained perspective on affective instability than those of previous personality disorder studies, this study points to patterns of affective experience characteristic of patients with borderline personality disorder.
Proximal Algorithms in Statistics and Machine Learning
(2015)

In this paper we develop proximal methods for statistical learning. Proximal point algorithms are useful in statistics and machine learning for obtaining optimization solutions for composite functions. Our approach exploits closedform solutions of proximal operators and envelope representations based on the Moreau, Forward-Backward, Douglas-Rachford and Half-Quadratic envelopes. Envelope representations lead to novel proximal algorithms for statistical optimisation of composite objective functions which include both non-smooth and non-convex objectives. We illustrate our methodology with regularized Logistic and Poisson regression and non-convex bridge penalties with a fused lasso norm. We provide a discussion of convergence of non-descent algorithms with acceleration and for non-convex functions. Finally, we provide directions for future research.
A novel bat algorithm with habitat selection and Doppler effect in echoes for optimization
(2015)

A novel bat algorithm (NBA) is proposed for optimization in this paper, which focuses on further mimicking the bats’ behaviors and improving bat algorithm (BA) in view of biology. The proposed algorithm incorporates the bats’ habitat selection and their self-adaptive compensation for Doppler effect in echoes into the basic BA. The bats’ habitat selection is modeled as the selection between their quantum behaviors and mechanical behaviors. Having considered the bats’ self-adaptive compensation for Doppler effect in echoes and the individual’s difference in the compensation rate, the echolocation characteristics of bats can be further simulated in NBA. A self-adaptive local search strategy is also embedded into NBA. Simulations and comparisons based on twenty benchmark problems and four real-world engineering designs demonstrate the effectiveness, efficiency and stability of NBA compared with the basic BA and some well-known algorithms, and suggest that to improve algorithm based on biological basis should be very efficient. Further research topics are also discussed. 2015 Elsevier Ltd. All rights reserved.
Use of genetic algorithms to solve production and operations management problems: A review
(2003)

Operations managers and scholars in their search for fast and good solutions to real-world problems have applied genetic algorithms to many problems. While genetic algorithms are promising tools for problem solving, future research will benefit from a review of the problems that have been solved and the designs of the genetic algorithms used to solve them. This paper provides a review of the use of genetic algorithms to solve operations problems. Reviewed papers are classified according to the problems they solve. The basic design of each genetic algorithm is described, the shortcomings of the current research are discussed and directions for future research are suggested.
A swarm optimization algorithm inspired in the behavior of the social-spider
(2013)

Swarm intelligence is a research field that models the collective behavior in swarms of insects or animals. Several algorithms arising from such models have been proposed to solve a wide range of complex optimization problems. In this paper, a novel swarm algorithm called the Social Spider Optimization (SSO) is proposed for solving optimization tasks. The SSO algorithm is based on the simulation of cooperative behavior of social-spiders. In the proposed algorithm, individuals emulate a group of spiders which interact to each other based on the biological laws of the cooperative colony. The algorithm considers two different search agents (spiders): males and females. Depending on gender, each individual is conducted by a set of different evolutionary operators which mimic different cooperative behaviors that are typically found in the colony. In order to illustrate the proficiency and robustness of the proposed approach, it is compared to other well-known evolutionary methods. The comparison examines several standard benchmark functions that are commonly considered within the literature of evolutionary algorithms. The outcome shows a high performance of the proposed method for searching a global optimum with several benchmark functions.
Bat-Inspired Optimization Approach for the Brushless DC Wheel Motor Problem
(2012)

This paper presents a metaheuristic algorithm inspired in evolutionary computation and swarm intelligence concepts and fundamentals of echolocation of micro bats. The aim is to optimize the mono and multiobjective optimization problems related to the brushless DC wheel motor problems, which has 5 design parameters and 6 constraints for the mono-objective problem and 2 objectives, 5 design parameters, and 5 constraints for multiobjective version. Furthermore, results are compared with other optimization approaches proposed in the recent literature, showing the feasibility of this newly introduced technique to high nonlinear problems in electromagnetics.